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Models & Strategies

How the leading playbooks are behaving right now — and which stocks fit each one.

A hand-curated field guide, written July 2026 — an editorial read of recent market behaviour, not output of Otto's screener and not investment advice. Strategies age: what re-rated yesterday is rarely cheap today. Every ticker below opens Otto's numbers-first deep dive — check the snowflake before you believe the story.

1 · Capex & infrastructure

selective outperformance

Own the companies that build the country.

Otto's current matches computed 2026-08-09 · refreshes ~every 30 days

Screen: infrastructure/defence/utility sectors with a positive 6-month trend, ranked by that trend. Screened within our curated ~100-ticker universe — not the whole market. Rule output, not advice.

Read the full playbook — history & US read

The oldest playbook in markets: when a government or an industry commits to a decade of physical building — railways, grids, factories — the builders' order books fill years in advance. The strategy is simply to hold the companies collecting those orders while the spending cycle runs.

Read more: Capital expenditure — Investopedia ↗

In the US what's working

Traditional infrastructure moves slowly here, but three capex waves are real: the CHIPS Act, re-shoring of manufacturing, and above all the physical build-out behind AI. Data centres need power generation, cooling and grid equipment — and the companies supplying them have traded like growth stocks.

2 · Mega-cap quality growth

#1 in the US

Buy the undisputed leaders, pay up, hold on.

Otto's current matches computed 2026-08-09 · refreshes ~every 30 days

Screen: mega-caps (≥$200B / ₹2.5T) with 10%+ profit margins and growing revenue, ranked by margins + growth. Screened within our curated ~100-ticker universe — not the whole market. Rule output, not advice.

Read the full playbook — history & US read

"Quality growth" means fortress balance sheets, fat cash flows and pricing power — and accepting you'll rarely get them cheap. The modern twist: in a market as efficient as the US, simply holding the biggest winners has beaten hunting for hidden gems.

Read more: Quality investing — Wikipedia ↗

In the US what's working

US returns have been historically concentrated in a handful of mega-cap tech monopolies — the "Magnificent Seven" and the AI-adjacent chip and cloud names. The winning move was refusing to be clever: own the leaders.

3 · Pure price momentum

works, but algorithm-dominated

Buy what's already going up — and respect your stops.

Otto's current matches computed 2026-08-09 · refreshes ~every 30 days

Screen: +15% or better over 6 months and within 15% of the 52-week high, ranked by blended 3/6-month return. Screened within our curated ~100-ticker universe — not the whole market. Rule output, not advice.

Read the full playbook — history & US read

Momentum is the most stubborn anomaly in finance: winners keep winning longer than theory says they should. It works until the liquidity that feeds it turns — which is why position sizing and exits matter more than entries.

Read more: Momentum investing — Wikipedia ↗

In the US what's working

US momentum is heavily algorithmic. Trend-following has paid best riding large-cap structural uptrends with tight risk management, to dodge sudden machine-driven reversals.

4 · The value re-rating play

value-trap risk

Buy what everyone ignored, wait for the story to change.

Otto's current matches computed 2026-08-09 · refreshes ~every 30 days

Screen: under 15× earnings (18× in India) AND rising over 6 months — cheap alone isn't enough, ranked by re-rating speed per unit of P/E. Screened within our curated ~100-ticker universe — not the whole market. Rule output, not advice.

Read the full playbook — history & US read

Classic value: buy statistically cheap assets and wait for the market to change its mind. The catch — cheap stays cheap without a catalyst. The strategy only pays when something forces the re-rating: policy, profits or scarcity.

Read more: Value investing — Investopedia ↗

In the US what's working

US deep value has underperformed for a decade — cheap American companies are usually cheap for a reason (legacy media, indebted industrials, disrupted retail). The exceptions: selective energy and financials during inflationary spikes.

5 · Quantitative smart beta

mainstream — yield & quality factors

Fire the stock picker, hire the rule.

Otto's current matches computed 2026-08-09 · refreshes ~every 30 days

Screen: a quality factor (ROE or margins ≥15%) blended with positive 6-month momentum — what rules-based factor funds buy. Screened within our curated ~100-ticker universe — not the whole market. Rule output, not advice.

Read the full playbook — history & US read

Factor investing sits between indexing and stock picking: buy whatever passes a transparent screen — momentum, quality, yield — rebalance on schedule, and let the rule remove the emotion. It's how retail money increasingly buys "strategy" itself.

Read more: Smart beta — Investopedia ↗

In the US what's working

Blended-factor ETFs — quality plus momentum — have performed exceptionally, and covered-call income funds have pulled in hundreds of billions from investors who want risk-adjusted yield more than pure upside.

The classic frameworks

CANSLIM, SEPA, Zulu, Darvas — built for the US decades ago, now fighting the algorithms at home.

CANSLIM

1933–2023
Portrait of William J. O'Neil William J. O'Neil Founded Investor's Business Daily · wrote How to Make Money in Stocks (1988)

Otto's current matches computed 2026-08-09 · refreshes ~every 30 days

Screen: quarterly earnings up 25%+ year-on-year with price within 10% of the 52-week high, per O'Neil's C and N. Screened within our curated ~100-ticker universe — not the whole market. Rule output, not advice.

Read the full playbook — O'Neil's story & the US read

Seven letters, one idea: buy fundamentally accelerating companies (Current and Annual earnings) exactly when the chart confirms institutional buying — the cup-and-handle breakout — and cut every loss at 7–8%, no exceptions.

Read more: CANSLIM — Investopedia ↗

In the US how it's holding up

High-frequency algorithms now hunt the obvious retail patterns — nudging price just past the breakout to trigger buying, then fading it to hit the tight stops. Outside the mega-cap AI leaders, US CANSLIM has been a choppy, low-win-rate ride.

SEPA / VCP

b. 1965
Portrait of Mark Minervini Mark Minervini US Investing Champion 1997 & 2021 · wrote Trade Like a Stock Market Wizard

Otto's current matches computed 2026-08-09 · refreshes ~every 30 days

Screen: above the 200-day trend with recent daily volatility at least 25% tighter than before, near the high — Minervini's contraction. Screened within our curated ~100-ticker universe — not the whole market. Rule output, not advice.

Editorial examples hand-picked, July 2026

Read the full playbook — Minervini's story & the US read

Specific Entry Point Analysis: wait for a leader's volatility to contract through successively tighter pullbacks — the Volatility Contraction Pattern — then enter as price pivots out on volume, risking fractions of a percent to make multiples.

Read more: minervini.com — the official site ↗

In the US how it's holding up

The same whipsaw problem as CANSLIM: tight pivots are exactly what fake-out algorithms feed on, so pure VCP in US mid caps has been rough outside the leadership names.

The Zulu Principle

1929–2015
Portrait of Jim Slater Jim Slater British financier · popularised the PEG ratio

Otto's current matches computed 2026-08-09 · refreshes ~every 30 days

Screen: PEG under 1.0 on 15–60% earnings growth, per Slater — spectacular growth is excluded as cyclical recovery, not compounding. Screened within our curated ~100-ticker universe — not the whole market. Rule output, not advice.

Read the full playbook — Slater's story & the US read

Slater's rule: specialise narrowly ("be a Zulu expert"), hunt small, under-researched companies growing EPS 15%+ — and only pay a PEG under about 0.75, so the growth costs less than it's worth.

Read more: Jim Slater — Wikipedia ↗

In the US how it's holding up

Nearly impossible in the US now: predictable 15% growers get priced to PEGs of 1.5+ instantly, and a genuinely low US PEG usually flags a value trap — one-off growth about to mean-revert. No honest picks here.

Darvas Box

1920–1977
Portrait of Nicolas Darvas Nicolas Darvas Ballroom dancer · wrote How I Made $2,000,000 in the Stock Market (1960)

Otto's current matches computed 2026-08-09 · refreshes ~every 30 days

Screen: within 3% of the highest close in our 5-year window and rising over 3 months — the top of the box. Screened within our curated ~100-ticker universe — not the whole market. Rule output, not advice.

Read the full playbook — Darvas's story & the US read

Darvas bought only stocks punching to new all-time highs on heavy volume, drew a "box" around each consolidation, bought the break of the box top and trailed his stop beneath it. No forecasts — price only.

Read more: Darvas Box theory — Investopedia ↗

In the US how it's holding up

Concentrated success: the boxes forced you into semiconductors, AI and GLP-1 names — which happened to be the biggest moves of the decade. Outside them, mostly sideways frustration.

The bottom line

United States

The winning US strategy has been recognising structural technological shifts — AI, cloud, data centres — and not being afraid to pay a premium for the highest-quality global monopolies.